Syntax parsing refers to a technique of determining a syntactical structure by parsing a given sentence according to a defined grammar structure. The syntax parsing method performs a parsing step by a syntax unit after morpheme parsing and tagging is finished. The syntax parsing method is largely divided into a rule-based parsing method and a statistics-based syntax parsing method.
The rule-based syntax parsing method parses a sentence by repetitively applying a relatively small number of rules. Accordingly, the rule-based syntax parsing method has a problem in that ambiguity processing is limited and parsing complexity increases due to an increase of ambiguity. Meanwhile, the statistics-based syntax parsing method can solve ambiguity by statistically modeling and applying correlation between vocabulary and a combination relation between syntaxes.
However, when applying a general statistics-based syntax parsing method, correctness in resolving ambiguity may be decreased due to a lack of learning data for extracting statistical information. Further, applying a general statistics-based syntax parsing method may have a problem in processing efficiency, for example, parsing speed decreases due to search of a massive statistic parameter space. Further, resolving ambiguity using statistic data has a problem in that it is not easy to add new knowledge or to enable a person to manage and tuning syntax parsing knowledge.
Therefore, a syntax parsing method that can reduce ambiguity likely generated when syntax parsing as much as possible is desperately needed. That is, a syntax parsing method that can reduce complexity of syntax parsing and that can effectively resolve ambiguity of syntax parsing is needed.